Impact of steam cooking on the chemical profile of table-stock sweetpotatoes with different carotenoids content.

Sweetpotatoes are a great source of carotenoids, which are important for human health and have attracted increasing attention. This study examined the impact of the steaming method on the contents of carotenoids, starch, soluble sugar, volatile organic compounds, and pasting properties of nine table-stock sweetpotatoes with different carotenoids content (from 3.21 to 233.46 µg/g). After steaming, carotenoids content was significantly decreased, among which G79 and P32 had the highest levels of 88.20 µg/g and 94.27 µg/g, respectively. The starch content of G42 decreased the most (20 %) with the highest peak viscosity (1764.33 cP), while the amylose content of P32 increased the most (12.59 %) with the lowest peak viscosity (441.33 cP). The contents of total starch and amylose were significantly correlated with sensory evaluation. G79 presented the best sensory evaluation and a sweet, delicious, and soft texture. A total of 57 volatile organic compounds were detected, among which benzene, a few aldehydes, and terpenoids contributed to the aroma of steamed sweetpotatoes. These results provide a theoretical foundation for future sweetpotato processing.

High-throughput phenotyping of nutritional quality components in sweet potato roots by near-infrared spectroscopy and chemometrics methods.

The lack of an efficient approach for quality evaluation of sweet potatoes significantly hinders progress in quality breeding. Therefore, this study aimed to establish a near-infrared spectroscopy (NIRS) assay for high-throughput analysis of sweet potato root quality, including total starch, amylose, amylopectin, the ratio of amylopectin to amylose, soluble sugar, crude protein, total flavonoid content, and total phenolic content. A total of 125 representative samples were utilized and a dual-optimized strategy (optimization of sample subset partitioning and variable selection) was applied to NIRS modeling. Eight optimal equations were developed with an excellent coefficient of determination for the calibration (R2C) at 0.95-0.99, cross-validation (R2CV) at 0.93-0.98, external validation (R2V) at 0.89-0.96, and the ratio of prediction to deviation (RPD) at 6.33-11.35. Overall, these NIRS models provide a feasible approach for high-throughput analysis of root quality and permit large-scale screening of elite germplasm in future sweet potato breeding.